Product design question
Design a news feature for Facebook.
- Meta
- Product design
- Medium
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Tests product design for content curation in a trust sensitive context: balancing relevance, source credibility, and misinformation risk.
How to approach it
- Define the user: someone wanting quick, trustworthy news updates relevant to their interests without wading through low quality sources.
- Identify the core tension: personalized relevance versus source credibility, since pure engagement optimization can favor sensational, less credible content.
- Propose the design: a curated news section ranking by a combination of topic relevance and publisher credibility signals, with clear source labeling.
- Address misinformation risk explicitly, requiring credibility scoring and rapid correction mechanisms for flagged stories.
- Define success: time spent on credible sources and reduction in flagged misinformation shares.
- Confirm with the interviewer whether this is a standalone tab or integrated directly into the main feed.
What a strong answer includes
- Balances relevance and credibility explicitly, ranking news by a combined score of topic match and publisher trustworthiness rather than engagement alone.
- Proposes clear source labeling, showing publisher name and credibility indicators directly on each story, building on lessons from past misinformation scrutiny.
- Addresses rapid correction, proposing a fast flagging and fact check partnership workflow for stories that turn out to be false.
- Sets a measurable goal, for example a stated increase in time spent on credible sources alongside a reduction in flagged misinformation shares.
Common mistakes
- Optimizing purely for engagement, which risks amplifying sensational or low credibility content given Facebook's past misinformation issues.
- Ignoring the need for transparent source labeling that lets users judge credibility themselves.
Likely follow-up questions
- How would you score publisher credibility without appearing to favor certain viewpoints?
- How would you handle a story that goes viral before it can be fact checked?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop